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Pursuit of simplicity. Often developers looking at the short run think that just putting the static HTML into their servlet will be easier or simpler because everything for the response is in one place. In the very short run, this assumption is probably correct. In the long run though, it is a major issue for maintenance and enhancement.

Inequality (2.33) is a consequence of (2.25) because (u E{MT })/u 1 as u + . Grosso modo, this says that the tail of the distribution of the random

0.532 0.274 0.656 0.446 0.481 0.296 0.643 0.295 0.641 0.247 0.564 0.322 0.679 0.295 0.49 0.324 0.642 0.232 0.462 0.133 0.587 0.341 0.478 0.353 0.59 0.313

you have a perfectly functional label distribution protocol (LDP) is unnecessary. The great thing for network operators is that both groups have developed implementations of their drafts. Martini is more widely implemented than L2VPN so if you are looking for interoperability in a multi-vendor environment, Martini may be the easier choice. If you have only one brand of PE, but another brand of P LSR, then running L2VPN is a reasonable alternative.

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gravity, and is typically measured by attaching a weight at one end of a sample and measuring the long-term elongation or by suspending a sample between two supports and measuring the long-term sag that gravity causes. Stress relaxation is a measure of the decrease in stress that occurs when a sample is elongated rapidly to constant strain. Shear rate ( ) or velocity gradient (93) is the rate at which the molecules ow relative to one another or D d /dt 3.51

0.86 0.71 33.6 44.8

Fresnel s equations, that there should be a small spot of brightness directly behind a solid object in the path of a light beam. This, said Poisson, was clearly ridiculous, the imagining of a feeble intellect. But Poisson s attempt to mock Fresnel back red. Another successful scientist, Dominique Fran ois Jean Arago, put Poisson s ridicule to the test. He shone a light at a small target and found a bright spot behind it, exactly where Fresnel s equations predicted it would be. The road-builder was vindicated. By now Newton s theory was like a punch-drunk boxer, still standing, not realizing that he has already been knocked out. Young and Fresnel had made the particle theory untenable; from now on the only acceptable view of light would be as a wave. The next great challenge was to discover how light worked, what made it travel at such an immense speed what it truly was. It took a remarkable man and his terri ed friend to give the rst unexpected glimpse of light s innermost secret.

for the existence of the Fourier transform are given in Section 2.4. The properties of the Fourier transform are summarized in Section 2.5. The Fourier transform discussed so far has a complex exponential kernel. It is actually possible to de ne the Fourier transform as a real transform with cosine and sine kernel functions. The resulting real Fourier transform is sometimes more useful. The 1-D real Fourier transform is discussed in Section 2.6. Amplitude and phase spectra of the 1-D Fourier transform are de ned in Section 2.7. Especially in optics and wave propagation applications, the 2-D signals sometimes have circular symmetry. In that case, the Fourier transform becomes the Hankel transform in cylindrical coordinates. The Hankel transform is discussed in Section 2.8.

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Dependent interviewing questions are typically classified as either proactive or reactive (Brown et al., 1998). With reactive DI, information fed forward from the previous interview is used to carry out edit checks during the interview; with proactive DI, previous information is used to determine question routing or wording. This broad classification encompasses a number of design features. The following conceptualisation of the different design options and their effects is based on a review of current practices and research, where the classification of designs was inspired by Pascale and Bates (2004) description of DI questions in the US Survey of Income and Program Participation (SIPP). Unless stated otherwise, examples are taken from the Improving Survey Measurement of Income and Employment study, described in Section 6.4.

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Hence, the Fourier transform of h(x,y) equals H1 fx H2 fy . The Fourier transform of h1(x) is given by

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